Mesh adaptation in finite element modelling of heat transport processes

Mesh adaptation in finite element modelling of heat transport processes Barbara Głut, Tomasz Jurczyk, Maciej Pietrzyk AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2001.2.0008 Abstract: The paper focuses on the problem of generation of anisotropic meshes and mesh adaptation for simulation of processes using the finite element method. The technique based on the Delaunay triangulation … Read more

Numerical modelling of solidification of castings. Sequential and parallel computer simulations

Numerical modelling of solidification of castings. Sequential and parallel computer simulations Ryszard Parkitny, Roman Wyrzykowski, Norbert Sczygiol, Arkadiusz Nagórka, Tomasz Olas, Grzegorz Szwarc Czestochowa University of Technology . DOI: https://doi.org/10.7494/cmms.2001.2.0009 Abstract: The work concerns numerical modelling of solidification of castings. Enthalpy formulations were used for mathematical description of solidification. Special attention was paid to the possibility … Read more

Application of higher order statistical factors and hamming’s artificial neural network to classification of material microstructure

Application of higher order statistical factors and hamming’s artificial neural network to classification of material microstructure Alexander Mikhalyov, Denis Mikhalyov National Academy of Sciences of Ukraine. DOI: https://doi.org/10.7494/cmms.2001.2.0010 Abstract: The method of classification of material microstructure accounting for texture is presented in the paper. The texture is defined as orientation of elements in three dimensions. … Read more

Problem of selection of proper architecture for neural network

Problem of selection of proper architecture for neural network Ryszard Tadeusiewicz AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2001.1.0001 Abstract: Review of problems connected with applications of artificial neural networks in generally understood metallurgy is discussed in the paper. Conditions, which particular tasks impose on the selection of the network architecture, are pointed out. These … Read more

Selection of neural network structure in real time control systems

Selection of neural network structure in real time control systems Krzysztof Kołek, Wojciech Mitkowski AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2001.1.0002 Abstract: In this paper example applications of neural networks for controlling laboratory models are presented. Two structures of neural controllers are considered. The neural networks are applied as neural controllers for three real … Read more

Application of artificial neural networks to classification of quality of ingots after continuous casting

Application of artificial neural networks to classification of quality of ingots after continuous casting Władysław Zalecki AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2001.1.0003 Abstract: The paper present primary results on an application of artificial neural networks to predictions of the influence of technological parameters of continuous casting on the quality of casted ingots. Development … Read more

Application of artificial neural network to an assessment of influence of residual microalloing elements on mechanical properties of steel products

Application of artificial neural network to an assessment of influence of residual microalloing elements on mechanical properties of steel products Roman Kuziak1, Władysław Zalecki1, Jan Kusiak2 1Instytut Metalurgii Żelaza, ul. K. Miarki I 2, 44-100 Gliwice. 2AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2001.1.0004 Abstract: The work presents some results of the research connected with … Read more

Identification of the experiment plan for neuron approximation

Identification of the experiment plan for neuron approximation Roma Górecka , Jacek Pietraszek, Zbigniew Polański AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2001.1.0005 Abstract: The paper describes an application of the SDM method (sequence data modification) to searching for an optimum structure of training data set (experiment plan) in a statical neuron approximation. Cite as: … Read more